US 6215827 B1 Abstract A system and method to measure channel quality in terms of signal to interference plus noise ratio for the transmission of coded signals over fading channels in a communication system. A Viterbi decoder metric for the Maximum Likelihood path is used as a channel quality measure for coherent and non-coherent transmission schemes. This Euclidean distance metric is filtered in order to smooth out short term variations. The filtered or averaged metric is a reliable channel quality measure which remains consistent across different coded modulation schemes speeds. The filtered metric is mapped to the signal to interference plus noise ratio per symbol using a threshold based scheme. Use of this implicit signal to interference plus noise ratio estimate is used for the mobile assisted handoff in a cellular system, power control and data rate adaptation in the transmitter.
Claims(14) 1. A method for determining a signal to interference plus noise ratio, comprising the steps of:
establishing a set of path metrics corresponding to a set of predetermined signal to interference plus noise rations;
receiving a digital signal;
determining a path metric for said digital signal by establishing a set of signal to interference plus noise ratio values that correspond to a set of predetermined short term average of metric values and averaging a decoded path metric; and
mapping said path metric to said signal to interference plus noise ratio in said set of predetermined signal to interference plus noise ratios.
2. The method of claim
1, wherein said digital signal is a coded signal.3. The method of claim
1 wherein said digital signal is a trellis coded signal.4. The method of claim
1 wherein the step of determining a path metric for said digital signal, further comprises the steps of:establishing a set of signal to interference plus noise ratio values corresponding to a set of predetermined short term average of metric values, said short term average of metric values defined as M/μ;
determining a decoded path metric from said received digital signal using a decoder, said decoded path metric defined as m
_{i}; averaging m
_{i}; storing in a memory unit said average decoded path metric, said average decoded path metric defined as μ; and
determining an estimated Euclidean distance metric defined as M
_{i}. 5. The method of claim
4 wherein the step of determining the estimated Euclidean distance metric is performed using the following equation:_{i} =aM_{i-1}+(1-a)m _{l } Where said estimated Euclidean distance metric is defined as Mi and α is a predetermined filter coefficient which is greater than zero and less than 1.0.
6. The method of claim
5 including the steps of:determining a standard deviation of M
_{i}; determining average metric thresholds defined as σ
_{low }and σ_{high }based on said standard deviation of M_{i}; determining a value for M
_{i}/μ by dividing said value of M_{i }by said value of μ; mapping said value of M
_{i}/μ to a minimum value of said corresponding signal to interference plus noise ratio if M_{i}/μ is less than σ_{low}; mapping said value of M
_{i}/μ to a maximum value of said corresponding signal to interference plus noise ratio if M_{i}/μ is greater than σ_{high}; and mapping said value of M
_{i}/μ to said corresponding signal to interference plus noise ratio. 7. The method of claim
4 wherein said decoder is a Viterbi decoder for the maximum likelihood path.8. A system for determining a signal to interference plus noise ratio, comprising:
means for establishing a set of path metrics corresponding to a set of predetermined signal to interference plus noise ratios;
means for receiving a digital signal;
means for determining a path metric for said digital signal by establishing a set of signal to interference plus noise ratio values that correspond to a set of predetermined short term average of metric values and averaging a decoded path metric; and
means for mapping said path metric to said signal to interference plus noise ratio in said set of predetermined signal to interference plus noise ratios.
9. The system of claim
8, wherein said digital signal is a coded signal.10. The system of claim
8 wherein said digital signal is a trellis coded signal.11. The system of claim
8 wherein the means for determining a path metric for said digital signal, further comprises:means for establishing a set of signal to interference plus noise ratio values corresponding to a set of predetermined short term average of metric values, said short term average of metric values defined as M
_{i}/μ; means for determining a decoded path metric from said received digital signal using a decoder; said decoded path metric defined as m
_{i}; means for averaging m
_{i}; and means for storing in a second memory unit said average decoded path metric, said average decoded path metric defined as μ; and
means for determining an estimated Euclidean distance metric defined as M
_{i}. 12. The system of claim
11 wherein the means for determining the estimated Euclidean distance metric is performed using the following equation:_{i} =aM_{i-1}+(1-a)m _{l } where said estimated Euclidean distance metric is defined as M
_{l }and α is a predetermined filter coefficient which is greater than zero and less than 1.0. 13. The system of claim
12 further comprising:means for determining a standard deviation of M
_{i}; means for determining average metric thresholds defined as σ
_{low }and σ_{high }based on said standard deviation of M_{i}; means for determining a value for M
_{i}/μ by dividing said value of M_{i }by said value of μ; means for mapping said value of M
_{i}/μ to a minimum value of said corresponding signal to interference plus noise ratio if M_{i}/μ is less than σ_{low}; means for mapping said value of M
_{i}/μ to a minimum value of said corresponding signal to interference plus noise ratio if M_{i}/μ is less than σ_{high}; and means for mapping said value of M
_{i}/μ to said corresponding signal to interference plus noise ratio. 14. The system of claim
11 wherein said decoder is a Viterbi decoder for the maximum likelihood path.Description This application is a continuation-in-part of U.S. patent application Ser. No. 08/921,454, filed Aug. 24, 1997, now U.S. Pat. No. 6,108,374, entitled “System and Method for Measuring Channel Quality Information”, which is not admitted to be prior art by its mention in the background section. The present invention relates generally to digital communication systems and, more particularly, to communications systems which utilize digital transmission schemes. As communication systems continue to grow worldwide at a rapid pace, the need for frequency spectrum efficient systems that accommodate both the expanding number of individual users and the new digital features and services such as facsimile, data transmission, and various call handling features is evident. As an example, current wireless data systems such as the cellular digital packet data (CDPD) system and the IS-130 circuit switched time division multiple access data system support only low fixed data rates that are insufficient for several applications. Since cellular systems are engineered to provide coverage at the cell boundary, the signal to interference plus noise ratio (abbreviated as SIR, SNR, or C/(I+N)) over a large portion of a cell is sufficient to support higher data rates. Existing adaptive data rate schemes using bandwidth efficient coded modulation are currently being proposed for increasing throughput over fading channels such as those encountered in mobile radio wireless systems. However, these schemes do not dynamically adjust the coded modulation to adapt to the channel conditions. Coded modulation schemes with different bandwidth efficiencies have different error rate performances for the same SIR per symbol. As result, at each SIR, the coded modulation scheme that results in the highest throughput with acceptable retransmission delay is desired. Therefore, the detection of channel quality in terms of SIR or achievable frame error rate is very important. As an example, fast and accurate methods to measure either the SIR or to estimate the FER are not available for cellular systems. Thus, there is a need to determine the channel quality based on the measurements, or metrics, of the SIR or the achievable frame error rate (FER) for the time varying channel. The difficulty in obtaining these metrics in communications systems such as cellular systems is based on the time varying signal strength levels found on the cellular channel. These time varying effects, referred to as fading and distance dependent loss, are the result of the movement of the mobile station (cellular phone) relative to the base station (also known as a cell site). Some recent schemes propose a short-term prediction of the FER, but not the SIR, using the metric for the second best path in a Viterbi decoder. This metric is computationally very intensive and reacts to short term variations in fading conditions. Therefore, there is a need, for an efficient and accurate method for measuring the channel quality in terms of the SIR in a communication system. Thus, there is a need to determine the channel quality of a communication system based on the measurements (metrics) of the SIR or the achievable frame error rate (FER) for the time varying channel in a digital transmission scheme to obtain a quick and reliable indicator of SIR in noise limited, interference limited and delay spread environments. This need extends for example, to coherent schemes such as M-ary phase shift keying (M-PSK) signaling and non-coherent schemes such as M-DPSK signaling It is also important to measure channel quality, in terms of SIR or FER, for the purpose of mobile assisted handoff (MAHO) and power control. However, FER measurements are usually very slow for the purpose of rate adaptation, power control and handoff. FER as a channel quality metric is slow because it can take a very long time for the mobile to count a sufficient number of frame errors. Therefore, there is a need for a robust short-term channel quality indicator that can be related to the FER. As a result, channel quality metrics such as symbol error rate, average bit error rate and received signal strength measurements have been proposed as alternatives. The IS-136 standard already specifies measurement procedures for both bit error rate and received signal strength. However, these measures do not correlate well with the FER, or the SIR, which is widely accepted as the meaningful performance measure in wireless systems. Also, received signal strength measurements are often inaccurate and unreliable. Thus, the SIR is a more appropriate as a handoff metric near the cell boundary where signal quality is rapidly changing. The present invention is directed to overcoming, or at least reducing the effects of one or more of the problems set forth above. This invention and methods are directed to determining the SIR for a digital communication system with a fading channel. While the following examples are directed to wireless communications such as cellular telephones the invention and methods descried apply equally well to non-wireless communications. In this invention, the above problems discussed in the background of the prior art are solved, and a number of technical advances are achieved in the art by use of the appropriate weighted decoder metric for the maximum likelihood path as a measure of the SIR per symbol. In accordance with one aspect of the present invention a system and method is provided for determining the path metrics of the communication system corresponding to a set of predetermined SIR values. A digital signal is received and a path metric determined for the digital signal. Mapping of the path metric is provided to a corresponding SIR in the set of predetermined SIR values. These and other features and advantages of the present invention will become apparent from the following detailed description, the accompanying drawings and the appended claims. While the invention is susceptible to various modifications and alternative forms, specific embodiments have been shown by way of example in the drawings and will be described in detail. However, it should be understood that the invention is not intended to be limited to the particular forms disclosed. Rather, the invention is to cover all modifications, equivalents and alternatives falling within the spirit and scope of the invention as described in the appended claims. The advantages of this invention will become apparent upon reading the following detailed description and upon reference to the drawings in which: FIG. 1 is a graphical representation of three cell sites within a cluster; FIG. 2 is a block diagram of both the base station and the mobile station transmitters and receivers for the present invention; FIG. 3 is a block diagram of a coherent decoder system for present invention; FIG. 4 is a block diagram of a non-coherent decoder system for present invention; FIG. 5 is a graph having a curve, with the vertical scale representing the average Viterbi decoder metric and the horizontal scale representing the time slot number; FIG. 6 is a graph having a curve, with the vertical scale representing the average Viterbi decoder metric and the horizontal scale representing the SIR; FIG. 7 is a graph having a curve, with the vertical scale representing the long term average of the channel quality metric and the horizontal scale representing the SIR for the voice limited case, with no fading interference; FIG. 8 is a graph having a curve, with the vertical scale representing the long term average of the channel quality metric and the horizontal scale representing the SIR for the interference limited case, with a single dominant interferer at 20 dB above the background noise level; FIG. 9 is a graph having a curve, with the vertical scale representing the SIR average error in dB and the horizontal scale representing the averaging duration for different Doppler frequencies and 0 dB of interference; FIG. 10 is a graph having a curve, with the vertical scale representing the SIR average error in dB and the horizontal scale representing the averaging duration for different Doppler frequencies and for the interference limited case, with a single dominant interferer at20 dB above the background noise level; FIG. 11 is a flow diagram illustrating the steps performed during the process of determining the SIR using the lookup table and adjusting the coded modulation scheme used by the system; FIG. 12 is a flow diagram illustrating the steps performed during the process of determining the SIR using the linear prediction and adjusting the coded modulation scheme used by the system; FIG. 13 is a graph having three curves, with the vertical scale representing the {overscore (FER)} and the horizontal scale representing the SIR; FIG. 14 is a table of values for a conservative mode adaptation strategy based on a Viterbi algorithm metric average; FIG. 15 is a table of values for an aggressive mode adaptation strategy based on a Viterbi algorithm metric average; FIG. 16 is a block diagram of both the base station and the mobile station transmitters and receivers for the implementation of an adaptive coding scheme; and FIG. 17 is a block diagram of both the base station and the mobile station transmitters and receivers for the implementation of a mobile handoff scheme and a power control scheme. Turning now to the drawings and referring initially to FIG. 1, a plurality of cells The boundaries FIG. 2 is a block diagram for the schematic of the base station Thus, the information rate may be varied by transmitting at a fixed symbol rate (as in IS-130/IS-136), and changing the bandwidth efficiency (number of information bits per symbol) using a choice of coded modulation schemes. However, coded modulation schemes with different bandwidth efficiencies have different error rate performance for the same SIR per symbol. At each SIR, the coded modulation scheme is chosen which results in the highest throughput with acceptable FER and retransmission delay. Therefore, detection of channel quality in terms of SIR or achievable FER is very important for this invention. Both the SIR and FER as channel quality metrics can be derived from the appropriately weighted cumulative Euclidean distance metric corresponding to a decoded received sequence. A block diagram of a encoder and decoder for use with a coherently modulated system in accordance with the invention is shown in FIG. 3. A transmitter The received symbol at the k
where s The Viterbi algorithm circuit of the MLD where a While FIG. 3 describes the invention using a coherent modulation system such as M-PSK or M-QAM, the invention also applies a similar metric computational method to a non-coherent modulation system. In the coherent M-PSK system of FIG. 3, the computation of the Euclidean distance metric assumes that the signals are coherently demodulated, and that an estimate of the channel coefficients is available to the receiver. However, a number of useful systems are designed using M-ary differential phase shift keying (M-DPSK) constellations, which are non-coherent systems. M-DPSK systems such as in the IS-136 standard allow a much simpler receiver structure compared to a coherent system of FIG. 3 because M-DPSK signals are often differentially demodulated prior to decoding. However, at present, like the M-PSK systems there is no fast accurate method to measure either the SIR or to estimate the FER in M-DPSK systems. And unlike the coherent system described in FIG. 3, the determination of the Euclidean distance metric for M-DPSK signals is not directly an accurate measure of the SIR. FIG. 4 describes an alternative example that uses an appropriately weighted or scaled Euclidean distance metric for M-DPSK signals which obtains a quick and reliable indicator of SIR in noise limited, interference limited and delay spread environments. FIG. 4 shows a block diagram of an encoder and decoder for a M-DPSK system. Within the transmitter The received symbol {r
where s
where r A Maximum Likelihood Decoder (MLD) In the Viterbi decoder the set of transmitted M-ary sequences can be mapped on to a trellis state transition diagram. The Viterbi algorithm is used to do a sequential search for the maximum likelihood path through the trellis. However, other realizations, other than the Viterbi decoder are possible for the MLD As a Viterbi algorithm circuit, the MLD associates an incremental Euclidean distance metric with each trellis branch transition and tries to find the transmitted M-ary sequence {{circumflex over (d)} At To determine the SIR metric the decoded data sequence {â ; or alternatively, which is easier to compute and yields a better estimate at high SIR values. Thus, in accordance with at least two aspects of the present invention, the Viterbi decoder is used to derive the channel quality information from the cumulative Euclidean distance metric, for both the coherent and non-coherent systems, corresponding to the decoded trellis path for each block. However, as noted earlier, the Euclidean distance metric has large variations from one block to another in the presence of a fading channel. Thus smoothing, such as averaging, of these variation is required to obtain a good estimate of the metric. A small cumulative Euclidean distance metric would indicate that the received sequence is very close to the decoded sequence. For well-designed trellis codes, this situation would only occur under good channel conditions with high SIR. Under poor channel conditions, the metric is much higher. Thus, a good estimate of the metric can be obtained at the i
for a greater than zero and less than 1.0, where m FIG. 5, illustrates a graph having a four curves, with the vertical scale representing the average Viterbi decoder metric M FIG. 6 shows a graph having four curves, with the vertical scale representing the long term average Viterbi decoder metric μ (the expected value of M The long term cumulative metric average μ and the SIR satisfy the empirical relationship where E where the target metric, μ, is obtained from The thresholds, σ FIGS. 7 and 8 show the long term average of the channel quality metric for a non-coherent system, as a function of SIR for a rate 5/6 coded DQPSK scheme in noise limited (I=0 in C/(N+I) thus C/N) and interference limited environments respectively. An IS-130/IS-136 time slot structure is assumed, and the trellis is terminated at the end of each time slot pair. In FIG. 7 the vertical axis represents the values of the long term average of the channel quality metric and the horizontal axis represents the SIR values in a noise limited environment C/N. The C/N ranges from 14 dB to 30 dB in steps of 2 dB. Each curve represents a different combination of the coding scheme and ƒ Additionally, FIG. 8 shows that the long term average channel quality metric is consistent across Doppler frequencies even with fading interferers. FIG. 8 shows plot of the long term average of the channel quality metric versus C/(I+N)(SIR) for a 4-DPSK (I/N=20 dB) coded scheme. The first line curve FIG. 9 shows the average error of the non-coherent metric. FIG. 9 shows the average error E|{Estimated C/(I+N)—Actual C/(I+N)}| (in dB) as a function of the average duration for a noise limited environment. Noise limited environment means that there are no interferers thus SIR is represented as C/N as in FIG. FIG. 10 shows the C/(I+N) estimation error for the case when a single dominant interfere is present. In this example, the noise is assumed to be 20 dB below the average interferer power thus I/N=20 dB. FIG. 10 has two line curves, In view of the invention as described in FIGS. 7-10, one skilled in the art will understand how to achieve the results described in FIGS. 5 and 6 for a M-DPSK transmission system and how to practice the invention in accordance with applications for rate adaptation, handoff and power control as described in the following description in this application. FIG. 11 is a flow diagram describing the steps performed by either the base station or the mobile station in determining the SIR from the average metric M The next step for n=1, 2, . . . K, where K determines the desired granularity. In step to the corresponding SIR values in the lookup table. Once the process of creating and storing the lookup table of μ In step The process continues to decision step is less than the predetermined threshold θ If the outcome of the determination step is greater than the predetermined threshold θ If, on the other hand, the outcome of the determination step is both less than the predetermined threshold θ in the lookup table. As a result, the system in step FIG. 12 is a flow diagram describing the steps performed by either the base station or the mobile station in determining the SIR from the average metric M In step for n=1, 2, . . . K, where K determines the desired granularity. In step to the corresponding SIR values in the lookup table. Once the process of creating and storing the lookup table of μ In step The process continues to decision step is less than the predetermined threshold θ If the outcome of the determination step is greater than the predetermined threshold θ If, on the other hand, the outcome of the determination step is both less than the predetermined threshold θ in the lookup table. As a result, the system in step This linear prediction approach helps the receiver use the current value and p-1 past values of the average metric to predict the channel quality metric D blocks in the future. Thus, this allows the receiver to react quickly to changes in the SIR. While SIR is the preferred performance measure in the present invention, it is well known that performance is often measured in terms of FER for the forward and reverse links. At a fixed SIR, the FER may often be different at different mobile speeds. In order to obtain a FER indication the SIR should be mapped to the average FER under some wide range of mobility. At each value of SIR, define the weighted sum where Σw As an example of an implemented rate adaptation system using the SIR measurements as a channel quality indicator. Let C FIG. 13, illustrates a graph having a three curves, with the vertical scale representing the {overscore (FER)} and the horizontal scale representing the SIR. The curves θ for j=2, 3, . . . , Q and for j=1, 2, . . . , Q-1 where r=1, 2, . . . , Q-j. For each j, the highest allowable value of r maximizes the throughput by permitting an operation at a higher rate in bits per symbol. Finally, filtering of the metric can be applied across the coded modulation schemes since the metric average, μ, is independent of the mobile speed or the coded modulation scheme. Thus, there is no need to reset the channel quality measure after the adaptation. Applying actual data to this example, FIG. 14 shows a table of values for a conservative mode adaptation strategy based on a Viterbi algorithm metric average. In, FIG. 14, C A block diagram of an adaptive rate system for the invention is shown in FIG. The encoder and modulation decision unit After the information is received at the receiver Next, the value of the Viterbi decoder metric A block diagram of a system using the SIR to do power control and determine mobile handoff is shown in FIG. The power control algorithm circuit After the information is received at the receiver Next, the value of the Viterbi decoder metric Additionally, the mobile assisted handoff decision circuit In conclusion, the following is a of the invention. The first part of the invention is an apparatus for adaptively changing the modulation schemes of a transmit data stream based on the measured SIR of a channel. The adaptive modulation schemes are implemented in a transmitter by an adaptive channel encoder and modulator. An encoder and modulation decision unit is connected to the transmitter adaptive channel encoder and modulator to determine the correct encoding and modulation scheme based on the information received at the receiver. Then a receiver channel decoder and demodulator is placed in radio connection with the transmitter adaptive channel decoder and demodulator through the channel. This receiver adaptive channel decoder and demodulator produces a path metric value which is averaged by an averaging circuit to produce an averaged path metric value. This averaged path metric value is then mapped through a mapping device to a SIR estimate value. The SIR estimate value is then input into the transmitter encoder and modulation decision unit to determine if the coding and modulation scheme should be changed in response to the SIR estimate value. It should be noted that the receiver channel decoder and modulator may be implemented in various way, however, in this example implementation a Viterbi decoder was used. The second part of the invention is an apparatus for implementing mobile assisted handoff based on the measured SIR of a channel. The mobile assisted handoff is implemented in a transmitter by a channel encoder and modulator. A receiver channel decoder and demodulator is in radio connection with the transmitter channel decoder and demodulator through a channel. The receiver channel decoder and demodulator produces a path metric value in response to the information received by the receiver which is averaged by an averaging circuit to produce an averaged path metric value. This averaged path metric value is then mapped through a mapping device to a SIR estimate value. A power control algorithm circuit is connected to the transmitter channel encoder and modulator which varies the power level of the transmitter in response to the SIR estimate value. Finally, the SIR estimate value is input into a mobile assisted handoff decision unit that determines if the mobile station should perform a handoff operation based on the SIR estimate value. As in the first part of the invention, it should again be noted that the receiver channel decoder and modulator may be implemented in various way, however, in this example implementation a Viterbi decoder was used. Additionally, this second part of the invention can be either implement at the mobile station or the base station. Please note that while the specification in this invention is described in relation to certain implementations or embodiments, many details are set forth for the purpose of illustration. Thus, the foregoing merely illustrates the principles of the invention. For example, this invention may have other specific forms without departing from its spirit or essential characteristics. The described arrangements are illustrative and not restrictive. To those skilled in the art, the invention is susceptible to additional implementations or embodiments and certain of the details described in this application can be varied considerably without departing from the basic principles of the invention. It will thus be appreciated that those skilled in the art will be able to devise various arrangements which, although not explicitly described or shown herein, embody the principles of the invention and are thus within its spirit and scope. The scope of the invention is indicated by the attached claims. Patent Citations
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